Mining operations are potential sources of airborne metal and metalloid contaminants through both direct smelter emissions and wind erosion of mine tailings. The warmer, drier conditions predicted for the Southwestern US by climate models may make contaminated atmospheric dust and aerosols increasingly important, with potential deleterious effects on human health and ecology. Fine particulates such as those resulting from smelting operations may disperse more readily into the environment than coarser tailings dust. Fine particles also penetrate more deeply into the human respiratory system, and may become more bioavailable due to their high specific surface area. In this work, we report the size-fractionated chemical characterization of atmospheric aerosols sampled over a period of a year near an active mining and smelting site in Arizona. Aerosols were characterized with a 10-stage (0.054 to 18 μm aerodynamic diameter) multiple orifice uniform deposit impactor (MOUDI), a scanning mobility particle sizer (SMPS), and a total suspended particulate (TSP) collector. The MOUDI results show that arsenic and lead concentrations follow a bimodal distribution, with maxima centered at approximately 0.3 and 7.0 μm diameter. We hypothesize that the sub-micron arsenic and lead are the product of condensation and coagulation of smelting vapors. In the coarse size, contaminants are thought to originate as aeolian dust from mine tailings and other sources. Observation of ultrafine particle number concentration (SMPS) show the highest readings when the wind comes from the general direction of the smelting operations site.

Mining operations, including crushing, grinding, smelting, refining, and tailings management, are a significant source of airborne metal and metalloid contaminants such as As, Pb and other potentially toxic elements. In this work, we show that size-resolved concentrations of As and Pb generally follow a bimodal distribution with the majority of contaminants in the fine size fraction (< 1 μm) around mining activities that include smelting operations at various sites in Australia and Arizona. This evidence suggests that contaminated fine particles (< 1 μm) are the result of vapor condensation and coagulation from smelting operations while coarse particles are most likely the result of windblown dust from contaminated mine tailings and fugitive emissions from crushing and grinding activities. These results on the size distribution of contaminants around mining operations are reported to demonstrate the ubiquitous nature of this phenomenon so that more effective emissions management and practices that minimize health risks associated with metal extraction and processing can be developed.

Mining operations are potential sources of airborne particulate metal and metalloid contaminants through both direct smelter emissions and wind erosion of mine tailings. The warmer, drier conditions predicted for the Southwestern US by climate models may make contaminated atmospheric dust and aerosols increasingly important, due to potential deleterious effects on human health and ecology. Dust emissions and dispersion of dust and aerosol from the Iron King Mine tailings in Dewey-Humboldt, Arizona, a Superfund site, are currently being investigated through in situ field measurements and computational fluid dynamics modeling. These tailings are heavily contaminated with lead and arsenic. Using a computational fluid dynamics model, we model dust transport from the mine tailings to the surrounding region. The model includes gaseous plume dispersion to simulate the transport of the fine aerosols, while individual particle transport is used to track the trajectories of larger particles and to monitor their deposition locations. In order to improve the accuracy of the dust transport simulations, both regional topographical features and local weather patterns have been incorporated into the model simulations. Results show that local topography and wind velocity profiles are the major factors that control deposition.

This study examines size-resolved physicochemical data for particles sampled near mining and smelting operations and a background urban site in Arizona with a focus on how hygroscopic growth impacts particle deposition behavior. Particles with aerodynamic diameters between 0.056 – 18 μm were collected at three sites: (i) an active smelter operation in Hayden, AZ, (ii) a legacy mining site with extensive mine tailings in Iron King, AZ, and (iii) an urban site, inner-city Tucson, AZ. Mass size distributions of As and Pb exhibit bimodal profiles with a dominant peak between 0.32-0.56 μm and a smaller mode in the coarse range (> 3 μm). The hygroscopicity profile did not exhibit the same peaks owing to dependence on other chemical constituents. Sub-micrometer particles were generally more hygroscopic than super-micrometer ones at all three sites with finite water-uptake ability at all sites and particle sizes examined. Model calculations at a relative humidity of 99.5% reveal significant respiratory system particle deposition enhancements at sizes with the largest concentrations of toxic contaminants. Between dry diameters of 0.32 and 0.56 μm, for instance, ICRP and MPPD models predict deposition fraction enhancements of 171%-261% and 33%-63%, respectively, at the three sites.

Wind erosion, transport and deposition of windblown dust from anthropogenic sources, such as mine tailings impoundments, can have significant effects on the surrounding environment. The lack of vegetation and the vertical protrusion of the mine tailings above the neighboring terrain make the tailings susceptible to wind erosion. Modeling the erosion, transport and deposition of particulate matter from mine tailings is a challenge for many reasons, including heterogeneity of the soil surface, vegetative canopy coverage, dynamic meteorological conditions and topographic influences. In this work, a previously developed Deposition Forecasting Model (DFM) that is specifically designed to model the transport of particulate matter from mine tailings impoundments is verified using dust collection and topsoil measurements. The DFM is initialized using data from an operational Weather Research and Forecasting (WRF) model. The forecast deposition patterns are compared to dust collected by inverted-disc samplers and determined through gravimetric, chemical composition and lead isotopic analysis. The DFM is capable of predicting dust deposition patterns from the tailings impoundment to the surrounding area. The methodology and approach employed in this work can be generalized to other contaminated sites from which dust transport to the local environment can be assessed as a potential route for human exposure.